class_docstr: Dataset builder that allows building a dataset without defining a class.
code: def __init__(
      self,
      *,
      name: str,
      version: utils.Version | str,
      features: feature_lib.FeatureConnector,
      split_datasets: Mapping[str, InputData],
      config: None | str | dataset_builder.BuilderConfig = None,
      data_dir: epath.PathLike | None = None,
      description: str | None = None,
      release_notes: Mapping[str, str] | None = None,
      homepage: str | None = None,
      citation: str | None = None,
      file_format: str | file_adapters.FileFormat | None = None,
      disable_shuffling: bool | None = False,
      **kwargs: Any,
  ):
      self.name = name
      self.VERSION = utils.Version(
          version
      )  # pylint: disable=invalid-name
      self.RELEASE_NOTES = release_notes  # pylint: disable=invalid-name
      if config:
          if isinstance(config, str):
              config = dataset_builder.BuilderConfig(
                  name=config,
                  version=version,
                  release_notes=release_notes,
              )
          self.BUILDER_CONFIGS = [
              config
          ]  # pylint: disable=invalid-name
      self._split_datasets = split_datasets
      self._feature_spec = features
      self._description = (
          description or "Dataset built without a DatasetBuilder class."
      )
      self._homepage = homepage
      self._citation = citation
      self._disable_shuffling = disable_shuffling
      super().__init__(
          data_dir=data_dir,
          config=config,
          version=version,
          file_format=file_format,
          **kwargs,
      )
  
imports: from __future__ import annotations
  from collections.abc import Iterable, Mapping
  import typing
  from typing import Any, Dict
  from absl import logging
  from etils import epath
  from tensorflow_datasets.core import dataset_builder
  from tensorflow_datasets.core import dataset_info
  from tensorflow_datasets.core import dataset_utils
  from tensorflow_datasets.core import download
  from tensorflow_datasets.core import features
  from tensorflow_datasets.core import file_adapters
  from tensorflow_datasets.core import split_builder
  from tensorflow_datasets.core import splits
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import apache_beam
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 1 to create a new AdhocBuilder object from inherited base classes: dataset_builder with example: obj = AdhocBuilder()